Ousted by Apple, Google plots next mapping coup

Google Inc.’s popular map app got booted from the software bundled with Apple Inc.’s new iPhone 5 — the casualty of an escalating feud between the Silicon Valley heavyweights — but the search company is still throwing plenty of research and development muscle into the technology.

Apple replaced Google’s app in its latest mobile operating system with its own (sharply criticized) Apple Maps. But Google reportedly plans to roll out a new app for Apple devices and continues to invest heavily in its mapping expertise because for hundreds of millions of users, Google Maps remains the go-to method to find their way.

So Google digital cartographers recognize it’s imperative that their maps know which Paris you’re talking about if they’re going to tell you how to get there.

If someone is searching on Google Maps for “Paris,” they’re probably looking for the city in France. Unless that user happens to be in Texas, in which case they’re probably looking for Paris, Texas, about 100 miles from Dallas. Or maybe they’re standing on The Strip in Las Vegas, in which case they want the Paris Hotel.

“Can you give me directions to Paris” might be obvious to a human being, but it takes a great deal of sophistication for online mapping technologies to accurately determine where they are in the physical world.

Of course, understanding what the user is searching for is only half the battle for Google Maps. Once the service understands where the user wants to go, the next challenge is to find the easiest routes to get them there, whether by car, foot, or public transit.

Handout/GoogleGoogle has been busy teaching its computers to comb through its vast collection of Street View photos and has developed technology that enables them to recognize street signs, turn restrictions and the locations of businesses.

So how does Google Maps figure out the best route for a user to take? How does it know which streets are marked ‘one way’ only, where there are left turn restrictions and which roads are separated by dividers or streetcar tracks?

The attempt to answer these questions led Brian McClendon, vice-president of Google Earth and Google Maps, and his team at the Mountain View, Calif.-based search titan, to launch Ground Truth in 2008, built on the back of the company’s Street View project.

“In 2008, we were in a situation where we were licensing third-party data and organizing it with search as best we could, but we weren’t able to do what we wanted with the data,” Mr. McClendon said in an interview.

“So we made a fundamental decision to go out and make our own maps and have our own data and be able to improve it in terms of both quality and detail. This has been a huge investment for us, focusing on both the data and the search quality.”

To create its digital maps, Google relies on all sorts of data from third-party providers, from satellite imagery and census data to bike trails from riding associations. With the Ground Truth project, Google has steadily been incorporating GPS data and images collected by its fleet of Street View cars, which have covered more than five million unique miles of roads in 3,000 cities in 40 countries.

With Ground Truth, Google has been busy teaching its computers to comb through its vast collection of Street View photos and has developed technology which enables them to recognize street signs, turn restrictions and the locations of businesses. Google combines that information with GPS data to help align the road information.

“It’s actually good GPS data and we make it much better by using computer vision to connect different photos to each other,” Mr. McClendon said. “We then run these computer vision algorithms to do extraction of street signs, speed limit signs, addresses and business logos, and then run these through automated recognition.”

These data can be uploaded immediately to the company’s road database, but if there’s a discrepancy, Google will send a Street View car operator to confirm what’s in the photos.

“The combination of heavy automation, with final human verification of the ambiguous pieces gives us a very high-quality data set that is derived from Street View imagery,” Mr. McClendon said.